enBanking sector concentration, competition and financial stability: the case of the Baltic countrieshttp://www.eestipank.ee/sites/eestipank.ee/files/publication/en/WorkingPapers/2017/wp07_2017.pdf
Bank of Estonia Working papers by Juan Carlos Cuestas, Yannick Lucotte and Nicolas ReiglBanking sector concentration, competition and financial stability: the case of the Baltic countries2017-08-29T12:37:00ZThis paper empirically assesses the potential nonlinear relationship between competition and bank risk for a sample of commercial banks in the Baltic countries over the period 2000-2014. Competition is measured by two alternative indexes, the Lerner index and the market share, while we consider the Z-score and loan loss reserves as proxies for bank risk. In line with the theoretical predictions of Martinez-Miera and Repullo (2010), we find an inverse U-shaped relationship between competition and financial stability.Banking sector concentration, competition and financial stability: the case of the Baltic countriesAbstracthttp://www.eestipank.ee/en/publication/working-papers/2017/72017-juan-carlos-cuestas-yannick-lucotte-and-nicolas-reigl-banking-sector-concentration-competitionFull texthttp://www.eestipank.ee/sites/eestipank.ee/files/publication/en/WorkingPapers/2017/wp07_2017.pdfNicolas ReiglJuan Carlos CuestasYannick LucotteJuan Carlos Cuestas, Yannick Lucotte and Nicolas Reigl2017-08-29Bank of Estonia Working papersG21G28G32L51Forecasting the Estonian Rate of Inflation using Factor Modelshttp://www.eestipank.ee/sites/eestipank.ee/files/publication/en/WorkingPapers/2016/wp08_2016.pdf
Bank of Estonia Working papers by Nicolas ReiglForecasting the Estonian Rate of Inflation using Factor Models2016-09-06T12:37:00ZThe paper presents forecasts of the headline and core inflation in Estonia with factor models in a recursive pseudo out-of-sample framework. The factors are constructed with a principal component analysis and are then incorporated into vector autoregressive forecasting models. The analyses show that certain factor-augmented vector autoregressive models improve upon a simple univariate autoregressive model but the forecasting gains are small and not systematic. Models with a small number of factors extracted from a large dataset are best suited for forecasting headline inflation. In contrast models with a larger number of factors extracted from a small dataset outperform the benchmark model in the forecast of Estonian headline and, especially, core inflation.Forecasting the Estonian Rate of Inflation using Factor ModelsAbstracthttp://www.eestipank.ee/en/publication/working-papers/2016/82016-nicolas-reigl-forecasting-estonian-rate-inflation-using-factor-modelsFull texthttp://www.eestipank.ee/sites/eestipank.ee/files/publication/en/WorkingPapers/2016/wp08_2016.pdfNicolas ReiglNicolas Reigl2016-09-06Bank of Estonia Working papersC32C38C53